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#' @title Debug Measure for Classification
#'
#' @name mlr_measures_debug_classif
#' @include Measure.R
#'
#' @description
#' This measure returns the number of observations in the [PredictionClassif] object.
#' Its main purpose is debugging.
#' The parameter `na_ratio` (`numeric(1)`) controls the ratio of scores which randomly
#' are set to `NA`, between 0 (default) and 1.
#'
#' @templateVar id debug_classif
#' @template measure
#'
#' @template seealso_measure
#' @export
#' @examples
#' task = tsk("wine")
#' learner = lrn("classif.featureless")
#' measure = msr("debug_classif", na_ratio = 0.5)
#' rr = resample(task, learner, rsmp("cv", folds = 5))
#' rr$score(measure)
MeasureDebugClassif = R6Class("MeasureDebugClassif",
inherit = Measure,
public = list(
#' @description
#' Creates a new instance of this [R6][R6::R6Class] class.
initialize = function() {
param_set = ps(na_ratio = p_dbl(0, 1, tags = "required"))
param_set$values = list(na_ratio = 0)
super$initialize(
id = "debug_classif",
param_set = param_set,
predict_type = "response",
range = c(0, Inf),
properties = "na_score",
label = "Debug Classification Measure",
man = "mlr3::mlr_measures_debug_classif"
)
}
),
private = list(
.score = function(prediction, ...) {
na_ratio = self$param_set$get_values()$na_ratio
if (na_ratio > runif(1L)) {
return(NA_integer_)
}
length(prediction$row_ids)
}
)
)
#' @include mlr_measures.R
mlr_measures$add("debug_classif", function() MeasureDebugClassif$new())
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